AI-Based Smart Home Intrusion Detection & Alert System Using Behavior Analysis and Face Recognition

Abstract: Home security has become a critical concern due to the increasing number of intrusion and theft incidents in residential areas. Traditional surveillance systems rely on manual monitoring and lack intelligent threat detection capabilities. This paper proposes an AI-based smart home intrusion detection and alert system that integrates face recognition and behavior analysis for continuous monitoring. The system captures real-time video data and processes it using deep learning algorithms to identify authorized and unauthorized individuals. It further analyzes human activity patterns to detect abnormal or suspicious behavior. Upon detecting an intrusion, instant alerts are sent to the homeowner through a mobile application. The proposed system enhances security by reducing response time and minimizing false alarms. It supports multi-modal inputs and ensures scalable deployment using IoT devices. The integration of artificial intelligence improves accuracy and automation in home surveillance. This system provides a reliable and efficient solution for modern smart home security.

Keywords: Smart Home Security, Intrusion Detection System, Artificial Intelligence, Face Recognition, Behavior Analysis, Computer Vision, Deep Learning, Continuous Monitoring, IoT-Based Surveillance, Real-Time Alert System